The invention relates generally to image processing. Particularly, this invention relates to a volume rendering techniques used in magnetic resonance imaging (MRI).
MRI systems have become ubiquitous in the field of medical diagnostics. In general, MRI imaging techniques are based on the interactions among a primary magnetic field, a radiofrequency (rf) field and time varying magnetic gradient fields that combine to influence nuclear spins within the subject of interest. Specific nuclear components, such as hydrogen nuclei in water molecules, have characteristic behaviors in response to external magnetic fields. The precession of spins of such nuclear components can be influenced by manipulation of the fields to obtain rf signals that can be detected, processed, and used to reconstruct a useful image.
The magnetic fields used to produce images in MRI systems include a highly uniform, static magnetic field that is produced by a primary magnet. A series of gradient fields are produced by a set of three gradient coils disposed around the subject. The gradient fields encode positions of individual volume elements or voxels in three dimensions. A radiofrequency coil is employed to produce an rf magnetic field, typically pulsed to create the required resonance signals. This rf magnetic field perturbs the spin system from its equilibrium condition, in which the spins precess at desired phases and frequencies. In response to the perturbation, the gyromagnetic materials emit rf signals that are detected by either the same transmitting rf coil, or by a separate receive-only coil. These signals are amplified, filtered, and digitized. The digitized signals are then processed using one of several possible reconstruction algorithms to reconstruct a useful image.
Many specific techniques have been developed to acquire MR images for a variety of applications. Typically, MR image processing entails multiple steps, one of which may involve reconstructing a three-dimension (3D) volume by using a mathematical transform such as a Fast Fourier Transform (FFT). The FFT is used to convert data in the frequency domain, otherwise known as k-space, into spatial domain data from which an image may be constructed. Constructed images may appear as 2-D slices of 3-D volumes, showing internal anatomical features in 2-D. Similarly, 3-D images may also be formed, however, such constructions directly from k-space are unfortunately computationally laborious and, therefore, quite lengthy. This is primarily due to the implementation of the FFT to a large k-space data set needed to reconstruct a 3-D image of an imaged volume. Moreover, applying image enhancing and image processing techniques, such as ray casting, shaded volume rendering, background contrast and so forth, after the 3-D image is constructed can be very lengthy as well. This is particularly so when some of the feature-enhancing methods require transforming the 3-D volume data back to the original k-space for further data manipulation. In some instances, the data may be transformed multiple times between frequency and spatial coordinate space before a final image is rendered, further increasing the computational time of the image processing.
Thus, there is a need for a system and method which reduces the amount of image processing time, particularly in converting k-space data into 2-D image data which ultimately forms a useful image. Further, there is a need for near real-time volume rendering methods in MRI, enabling rapid visualization of 2-D images generated from data MR data, some of which may be performed during an imaging procedure.